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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #357605

Research Project: Application Technologies to Improve the Effectiveness of Chemical and Biological Crop Protection Materials

Location: Crop Production Systems Research

Title: Comparing canopy hyperspectral reflectance properties of Palmer amaranth to okra and super-okra leaf cotton

Author
item Fletcher, Reginald
item Turley, Rickie

Submitted to: American Journal of Plant Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/22/2018
Publication Date: 12/25/2018
Citation: Fletcher, R.S., Turley, R.B. 2018. Comparing canopy hyperspectral reflectance properties of Palmer amaranth to okra and super-okra leaf cotton. American Journal of Plant Sciences. 9(13):2708-2718.

Interpretive Summary: Palmer amaranth is a major weed problem of cotton production systems in the southern United States. Hyperspectral remote sensing has shown promise as a tool for crop weed discrimination, and there is a growing interest in using the technology for identifying weeds in cotton production systems. ARS Scientists at Stoneville, MS used a hyperspectral sensor to develop light reflectance profiles of Palmer amaranth and cotton with different leaf shapes, okra and super- okra. They identified optimal wavelengths to use for differentiating Palmer amaranth and super-okra leaf cotton (2000 nm, 2180 nm). Results were not consistent for Palmer amaranth and okra leaf cotton. Commercially available sensors can be tuned to the optimal bands identified in this study, facilitating application of remote sensing technology for Palmer amaranth discrimination from super-okra leaf cotton and implementation of the technology as a decision support tool in weed management programs.

Technical Abstract: Palmer amaranth (Amaranthus palmeri S. Wats.) is a major weed problem of cotton (Gossypium hirsutum L.) production systems in the southern United States. Hyperspectral remote sensing has shown promise as a tool for crop weed discrimination, and there is a growing interest in using this technology for identifying weeds in cotton production systems. Information is lacking on differentiating Palmer amaranth from cotton with an okra leaf structure based on canopy hyperspectral reflectance properties. Two greenhouse studies were conducted to compare canopy hyperspectral reflectance profiles of Palmer amaranth to canopy hyperspectral reflectance profiles of okra and super-okra leaf cotton and to identify optimal regions of the electromagnetic spectrum for their discrimination. Ground-based hyperspectral measurements of the plant canopies were obtained with a spectroradiometer (400-2350 nm range). Analysis of variance (ANOVA, p = 0.05), Dunnett’s test (p = 0.05), and difference and sensitivity measurements were tabulated to determine the optimal wavebands for Palmer amaranth and cotton discrimination. Results were inconsistent for Palmer amaranth and okra leaf cotton separation. Optimal wavebands for distinguishing Palmer amaranth from super-okra leaf cotton were observed in the shortwave infrared region (2000 nm and 2180 nm) of the optical spectrum. Ground-based and airborne sensors can be tuned into the shortwave infrared bands identified in this study, facilitating application of remote sensing technology for Palmer amaranth discrimination from super-okra leaf cotton and implementation of the technology as a decision support tool in cotton weed management programs.